The present invention relates to a method and software for evaluating compressor stall/surge margin requirements and more particularly to using statistical analysis to identify the contribution each vital factor has on the compressor stall/surge margin requirements.
Efficient power generation equipment is highly in demand. Preferred power generation equipment consists of a gas turbine combined-cycle power plant utilizing a gas-turbine topping cycle and a Rankine-based bottoming cycle. This type of power generation equipment is preferred because of low costs and the continually improving operating efficiency of the gas turbine based combined cycle that leads to reduce the cost of the power produced.
These preferred industrial gas turbine systems are operated to achieve the goals of minimal parts count, operational simplicity, overall low costs, high combined cycle efficiency and high power output. An increase in the combined-cycle efficiency and power generated can be accomplished by elevating the firing temperature. For a given firing temperature, an optimal cycle pressure ratio exists that maximizes the combined-cycle efficiency. The optimal cycle pressure ratio, theoretically, trends higher with increasing firing temperature.
Typically in industrial gas turbine systems, axial compressors are subjected to the demand for increased pressure ratios. In addition, the compressor must also perform in an aerodynamically and mechanically stable manner over a wide range of mass flow rates that are associated with the varying power output characteristics of combined-cycle industrial gas turbine operation.
To meet these demands of the compressor, the operating compressor pressure ratio of an industrial gas turbine is typically set to a pre-specified margin away from the surge/stall boundary, know as the stall/surge margin. This margin is designed to avoid unstable compressor operation.
Conventionally, the stall/surge margin of the compressor is evaluated by identifying a list of factors that contribute to the stall/surge margin during operation of the industrial gas turbine system. The standard deviations of the individual factors are combined using root-sum-squares to determine the overall stall/surge margin standard deviation. The variability of the stall/surge margin can be caused by either variation from build to build or variation within any single industrial gas turbine system. The resulting overall stall/surge margin standard deviation is then multiplied by a risk factor that gives a determined stall/surge margin that has a low probability of a surge. Typically, the stall/surge margin represents a region where the industrial gas turbine system operates at a high efficiency with a very low probability for a surge. In conventional industrial gas turbines, once the stall/surge margin is determined, it is not modified over operational time or the operating conditions of the industrial gas turbine system.
Therefore, it is desired to determine the operational characteristics of an industrial gas turbine system that allow operation at the highest operational efficiency, with the highest power output and with low probability of a surge or stall. To achieve these operational goals, it is also desired to determine a stall/surge margin that allows the operating pressure ratio to be as close as possible to the surge/stall boundary. To ensure efficient and unproblematic operation in this region, it is further desired that each of the factors be accurately evaluated to determine the contribution of each factor on the stall/surge margin. In addition, it is desired that adjustment of the stall/surge margin be performed during operation of the industrial gas turbine system based on the evaluation of the each factor.
In one exemplary embodiment, a method for evaluating stall/surge margin for a machine of interest is provided. The method includes inputting data relating to desired operating conditions of the machine of interest. A plurality of vital factors is identified where each of the plurality of vital factors corresponds to the operation of the machine of interest. At least one of the plurality of vital factors is selected. Raw data relating the selected at least one of the plurality of vital factors is provided. A contribution of the selected at least one of the plurality of vital factors to the stall/surge margin is determined from at least the provided raw data and the input data related to the desired operating conditions of the machine of interest. The contribution of the plurality of vital factors to the stall/surge margin is statistically analyzed. A stall/surge margin is allocated based on the statistical analysis of the plurality of vital factors. An operating limit line is defined based on the allocation of the stall/surge margin.
In another exemplary embodiment, a computer readable medium is provided that contains instructions for controlling a computer system to perform a method. The method includes inputting data relating to desired operating conditions of the machine of interest. A plurality of vital factors are identified where each of the plurality of vital factors corresponds to the operation of the machine of interest. At least one of the plurality of vital factors is selected. Raw data relating the selected at least one of the plurality of vital factors is provided. A contribution of the selected at least one of the plurality of vital factors to the stall/surge margin is determined from at least the provided raw data and the input data related to the desired operating conditions of the machine of interest. The contribution of the plurality of vital factors to the stall/surge margin is statistically analyzed. A stall/surge margin is allocated based on the statistical analysis of the plurality of vital factors. An operating limit line is defined based on the allocation of the stall/surge margin.